One of the most well-established networks with a focus on face recognition is the VGGFace [1]}, introduced in 2015.
VGGFace is pre-trained on 2.6 million face images and achieves 98.95% accuracy on the Labeled Faces in the Wild (LFW) dataset [2]} under the face verification task.
Conversely to most works in the literature, we design an open-set face recognition approach following a face-verification strategy.
